Laser Line Scanner Alignment Utilizing Reference Points and a Common Direction Vector

The disclosed examples relate to aligning laser line scanners of a laser measurement system.

Laser measurement systems can utilize a plurality of laser line scanners arranged at different perspectives to obtain two-dimensional point clouds (depth and width) of a cross-section of a scanned object. Further, a series of two-dimensional point clouds obtained from the laser line scanners with linear motion can be combined to form a three-dimensional point cloud of the scanned object.

One example provides a laser measurement system comprising an alignment artifact attached to a global reference frame. The alignment artifact has a plurality of features, where each feature defines a corresponding reference point relative to the global reference frame. The laser measurement system further comprises a plurality of laser line scanners and a controller. The controller is configured to, for at least a first laser line scanner of the plurality of laser line scanners, obtain metadata comprising a set of expected locations of the corresponding reference points for a set of features from the plurality of features. The set of features comprises at least the features of the alignment artifact that are within a target view of the first laser line scanner during a scan. The controller is also configured to obtain a raw point cloud of the alignment artifact using the first laser line scanner within a first scanner reference frame, and to determine one or more scanned features from the raw point cloud. The control is further configured to determine a location of a corresponding scanned reference point for each scanned feature of the one or more scanned features to form a set of scanned locations of the corresponding scanned reference points. The controller is also configured to determine a first transformation matrix to transform coordinates between the first scanner reference frame and the global reference frame based at least upon the set of expected locations, the set of scanned locations, and a common direction vector for the plurality of laser line scanners. The controller is further configured to store the first transformation matrix for measurement of a scanned object.

This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter. Furthermore, the claimed subject matter is not limited to implementations that solve any or all disadvantages noted in any part of this disclosure.

As mentioned above, laser measurement systems utilize laser line scanners to obtain raw point clouds of a scanned object. Such laser line scanners are arranged with different locations and/or orientations to each other and the scanned object in order to scan the scanned object from different perspectives. To combine the raw point clouds from the different laser line scanners, some laser measurement systems transform the raw point clouds to a global reference frame. However, such transforms rely on a sufficiently accurate alignment of each laser line scanner relative to the global reference frame. Current methods of alignment can be inaccurate and time consuming. More particularly, the current methods find scanned planes for faces of an alignment artifact. Further, an iterative guess and check method is utilized to determine whether a transformation of the scanned planes match the geometry of the alignment artifact in the global reference frame. Such iterative guess and check methods can consume an undesired amount of compute time and/or compute resources.

Additionally, one or more of the laser line scanners may not be aligned with a system direction of travel of the laser measurement system. Such skew can result in divergent scanned data when the point clouds are transformed into the global reference frame. For example, when scanning a sphere, such skew would produce a scanned ellipsoid. Further, such divergence can increase further along the system direction of travel and may result in inaccurate measurements for the scanned object. As such, scans of long and skinny objects (e.g., an aircraft stringer) can be prone to such inaccuracies. However, the current methods of alignment do not address skew when aligning the laser line scanners.

Accordingly, examples are disclosed that relate to aligning laser line scanners utilizing reference points and a common direction vector for the laser line scanners. Briefly, the common direction vector is determined for a plurality of laser line scanners of a laser measurement system. Further, the common direction vector is mathematically used as a direction of travel for each of the plurality of laser line scanners during a scan. In such a manner, the common direction vector helps to address potential skew in the plurality of laser line scanners as will be discussed in detail below.

Additionally, when aligning a laser line scanner, an alignment artifact attached to a global reference frame is arranged in the laser measurement system. The alignment artifact comprises features that define corresponding reference points relative to the global reference frame. Further, the laser measurement system is configured to determine scanned locations of corresponding scanned reference points from a scan of the alignment artifact. Additionally, based at least upon the expected locations of the corresponding reference points and the scanned locations of the corresponding scanned reference points, a linear regression can determine a transformation matrix for the laser line scanner. This transformation matrix is utilized when the laser measurement system performs a scan for measurement. The linear regression can help to significantly reduce processing time and/or compute resources when determining a transformation matrix versus an iterative approach for finding the transformation matrix.

1 FIG. 100 102 102 102 102 100 100 schematically depicts an example laser measurement systemfor scanning an object. Here, a scan of the objectcan be utilized to measure the objectin three-dimensions, for example, as part of a production process. In some examples, the objectcan comprise an aircraft part, such as a stringer. In other examples, the laser measurement systemcan measure another suitable object. Examples of suitable objects include tubes, ducts, metal parts (e.g., aluminum, titanium, or steel parts), and composite parts (e.g., carbon fiber parts). As such, the laser measurement systemcan have applications in the aerospace industry, the automotive industry, rail applications, maritime applications, energy fields, engineering applications, and/or other suitable applications, for example, where inspection of tolerances is required during manufacture, service, and/or inspection.

102 104 100 106 108 110 112 102 102 104 114 1 FIG. 3 FIG. As can be seen, the objectis arranged relative to a global reference frame. Further, the laser measurement systemcomprises a plurality of laser line scanners.depicts, for the plurality of laser line scanners, a first laser line scanner, a second laser line scanner, a third laser line scanner, and a fourth laser line scanner. In other examples, a laser measurement system can include another number of laser line scanners, either fewer than or more than four. During a scan, the plurality of laser line scanners is configured to move relative to the objectto obtain a plurality of raw point clouds along a length of the object(depicted here as along the x-axis of the global reference frame). This movement is mathematically expressed using a common direction vectorfor the plurality of laser line scanners, as will be discussed with reference to.

106 102 102 116 106 106 108 102 110 112 104 102 100 104 106 104 100 108 110 112 During the scan, the first laser line scannerobtains a first raw point cloud of the objectat a cross-section of the objectthat is within a first target viewof the first laser line scanner. The first raw point cloud includes coordinates within a first scanner reference frame of the first laser line scanner. Likewise, the second laser line scannerobtains a second raw point cloud of the objectwithin a second target view. Similarly, the third and fourth laser line scanners,obtain corresponding raw point clouds. As previously mentioned, the raw point clouds are transformed to the global reference framefor measuring the object. More particularly, the laser measurement systemis configured to transform the coordinates of the first raw point cloud to the global reference framebased at least upon an alignment of the first laser line scannerrelative to the global reference frame. Likewise, the laser measurement systemis also configured to transform coordinates of the second, third, and fourth raw points based at least upon alignments of the corresponding second, third, and fourth laser line scanners,,.

100 106 108 110 112 104 102 106 114 108 110 112 114 104 104 114 2 FIG.B 3 FIG. Additionally, the laser measurement systemis configured to align the first laser line scanner, the second laser line scanner, the third laser line scanner, and/or the fourth laser line scannerto the global reference frame. These alignments are performed before a scan to measure the object. Briefly, during alignment of the first laser line scanner, a first transformation matrix of the first scanner reference frame is determined. The transformation matrix includes at least the common direction vector. Likewise, transformation matrices that are determined for the second, third, and fourth laser line scanners,,also include at least the common direction vector. An example of a transformation matrix is discussed with reference to. In such a configuration, the transformations from the scanner reference frames to the global reference framecan have straight scanner transformations so that they are not unintentionally diverging in the global reference frame. Thus, the common direction vectorhelps to address potential skew of the laser line scanners as will be discussed with reference to.

1 FIG. These alignments can be performed before each scan for measurement, and/or at another suitable interval. A suitable interval can be selected based at least upon observed alignment drift over time. For example, some conditions of a factory environment can change a position of one or more of the laser line scanners relative to each other over time, such as ambient temperature changes, for example.is illustrative. In other examples, the plurality of laser line scanners may have another arrangement relative to each other. In further examples, a laser measurement system may have another configuration.

2 2 FIGS.A andB 200 202 200 202 As previously mentioned, a laser measurement system is configured to transform coordinates between a scanner reference frame and a global reference frame utilizing a transformation matrix.schematically illustrate such a transformation between an example scanner reference frameand an example global reference frame. Here, the scanner reference framereflects an orientation and a location of a laser line scanner relative to the global reference frame.

2 FIG.A 200 204 In, the scanner reference frameincludes a scanner origin pointand vectors defining the x-, y-, and z-axes. These vectors can be expressed mathematically with [[{circumflex over (x)}][ŷ][{circumflex over (z)}]], and more specifically by the following matrix.

202 206 200 204 206 208 200 202 210 Likewise, the global reference frameincludes a global origin pointand vectors defining the x′, y′, and z′ axes. As can be seen, the scanner reference framehas a different location for the scanner origin pointthan the global origin point, depicted here with a translation line. Also, the scanner reference framehas a different orientation than the global reference frame, depicted here with a rotation line.

2 FIG.B 212 214 216 212 212 218 208 206 204 200 202 218 T In, an example transformation matrixis configured to transform a scanner coordinate(e.g., x, y, z) to a corresponding global coordinate(e.g., x′, y′, z′). The transformation matrixcan be used for any transformation matrix disclosed herein. Here, the transformation matrixcomprises a translation vectorbased at least upon the translation linefrom the global origin pointto the scanner origin point. This addresses a positional offset of the scanner reference framerelative to the global reference frame. Further, the translation vectorcan be mathematically expressed as {circumflex over (t)}=[x y z].

212 220 210 206 204 200 202 220 222 222 200 220 222 220 x z The transformation matrixalso comprises a rotation matrixbased at least upon the rotation linefrom the global origin pointto the scanner origin point. This addresses an orientation offset of the scanner reference framerelative to the global reference frame. Additionally, the rotation matrixincludes a common direction vector. As mentioned, each transformation matrix for a plurality of laser line scanners utilizes the common direction vectorto help address potential skew. Generally, a direction of travel of the scanner reference frameis mathematically defined along the y-axis. As such, the rotation matrixcomprises an x-rotation vector, the common direction vector, and a z-rotation vector. Mathematically, the rotation matrixcan be expressed with {circumflex over (R)}=[{right arrow over (R)} {right arrow over (d)} {right arrow over (R)}].

212 In view of the above, the transformation matrixcan be expressed with the following equation:

214 200 202 216 212 T T In such a manner, the scanner coordinatecan be transformed from the scanner reference frameto the global reference frameto form the corresponding global coordinatebased at least upon the transformation matrix. This transformation can be mathematically expressed using the following formula: [x′ y′ z′ 1]=[{circumflex over (T)}][x y z 1].

200 202 208 210 6 FIG. 2 2 FIGS.A andB As discussed, the scanner reference framecan be aligned with the global reference framebefore a scan for measurement. Briefly, such an alignment can determine a best fit of the translation lineand the rotation line. As used herein, the term “best fit” refers to determining one or more variables of a formula such that a value of differences between corresponding coordinates in a global reference frame and scanned coordinates in a scanner reference frame is within a desired range. An example method for determining a transformation matrix is discussed with reference to.are illustrative.

As previously mentioned, transformations between reference frames utilize a common direction vector to address potential skew in a plurality of laser line scanners of a laser measurement system. Specifically, a transformation matrix of a scanner reference frame utilizes the common direction vector as a y-rotation vector of a rotation matrix. Such a configuration helps to mathematically define a same direction of travel for each of the scanner reference frames. Additionally, the common direction vector for the plurality of laser line scanners can be determined during a calibration procedure of the laser measurement system. In some examples, the calibration procedure may be performed during initial installation of the laser measurement system.

3 FIG. 3 FIG. 300 302 304 302 306 308 306 310 312 304 314 310 316 306 314 300 306 314 300 schematically illustrates an example common direction vectorfor a plurality of laser line scanners. Here, the plurality of laser line scanners comprises a first laser line scannerand a second laser line scanner. In other examples, more than two laser line scanners may be used. As depicted, the first laser line scannerhas a first individual direction vectororientated along a y-axis of a first scanner reference frame. As can be seen, the first individual direction vectoris not aligned with a system direction of travel. Such misalignment results in first skew. Likewise, the second laser line scannerhas a second individual direction vectorthat is not aligned with the system direction of traveland thus, results in second skew. Additionally, the first individual direction vectorand the second individual direction vectordiverge away from each other and may result in skewed data when transforming raw point clouds to a global reference frame. Here, the common direction vectoris determined by finding an average of the first individual direction vectorand the second individual direction vector. In examples with more than two laser line scanners, the average of a corresponding plurality of individual direction vectors of a plurality of laser line scanners is found. In other examples, the common direction vectormay be determined in another suitable manner.is illustrative.

4 FIG. 400 100 400 402 402 illustrates a block diagram of an example laser measurement system. The laser measurement systemis an example of the laser measurement system. Here, a plurality of laser line scannersare configured to obtain raw point clouds as discussed. Such scans can be used to measure a portion of a scanned object and/or to align at least a first laser line scanner of the plurality of laser line scanners.

404 400 404 406 406 406 5 FIG. During alignment, an alignment artifactattached to a global reference frame is arranged in the laser measurement system. The alignment artifactcomprises a plurality of features. Further, each feature of the plurality of featuresdefines a corresponding reference point. In such a configuration, a plurality of the corresponding references points is arranged at expected locations within the global reference frame. In various examples, the plurality of featurescan include spheres, pyramids, cuboids, other polyhedrons, other suitable geometry that defines at least one corresponding reference point, and/or suitable combinations thereof. In examples using spheres, a sphere can define a corresponding center point as the corresponding reference point as discussed with reference to. In examples using pyramids, an apex of the pyramid can be used as the corresponding reference point.

400 408 410 404 410 412 406 414 412 410 412 402 408 416 416 416 212 408 9 FIG. The laser measurement systemalso includes a storage subsystem. Here, the storage subsystem comprises metadatarelated to the alignment artifact. Specifically, the metadatacomprises at least one set of featuresfrom the plurality of featuresthat are within a target view of the first laser line scanner. The metadata also includes a set of expected locationsof the corresponding reference points for the set of features. In the depicted example, the metadataincludes a corresponding plurality of the sets of featuresfor the plurality of laser line scanners. In other examples, metadata may have another configuration. The storage subsystemalso comprises a plurality of transformation matrices. More particularly, each transformation matrixis configured to transform coordinates between a selected scanner reference frame and the global reference frame. For example, the transformation matrixcan take the form of the transformation matrix. Further aspects of the storage subsystemare discussed with reference to.

418 400 402 418 416 402 418 410 402 418 418 416 414 416 402 418 402 418 418 418 408 6 7 FIGS.and 8 FIG. A controlleris configured to perform various operations of the laser measurement system, such as controlling the laser line scanners. As another example, the controlleris also configured to store the transformation matrixfound for the laser line scannerselected during alignment. Briefly, the controlleris configured to obtain the metadatapertaining to the target view of the laser line scanner. Further, the controlleris configured to form a set of scanned locations for each scanned feature found in a raw point cloud. The controlleris also configured to determine the transformation matrixbased at least upon the set of expected locationsand the set of scanned locations. The transformation matrixis also based upon a common direction vector for the plurality of laser line scannersas discussed. Example methods for alignment are discussed with references to. Additionally, the controlleris configured to measure a portion of a scanned object utilizing the plurality of laser line scannersas discussed with reference to. In some examples, the controllercan be implemented in circuits and/or firmware. In other examples, the controllercan be implemented as instructions executable by a processor. In such examples, the instructions for the controllercan be stored in the storage subsystem.

5 FIG. 500 500 502 500 504 500 504 504 504 506 As previously mentioned, a laser measurement system scans an alignment artifact during alignment of one or more laser line scanners.schematically depicts such an example alignment artifact. As depicted, the alignment artifactattached to a global reference frame. The alignment artifactcomprises a plurality of features in the form of a plurality of spheres, such as matte tooling balls, for example. The alignment artifactcomprises a sufficient number of the spheressuch that each laser line scanner of the laser measurement system can have at least three of the sphereswithin a target view during a scan. Additionally, the spheresare arranged with positional diversity around a cylinder object. In other examples, a plurality of features can be arranged around other suitable geometry. Examples of suitable geometries include a center pole, a cage, a center spiral, and/or another suitable shape that holds a plurality of features in three-dimensional space.

504 508 508 502 500 506 504 5 FIG. Each spheredefines a corresponding reference point in the form of a corresponding center point(illustrated as a point at which five lines intersect). In such a manner, each corresponding center pointis arranged at an expected location relative to the global reference frame. Additionally, a center point may be found for a sphere that is partially within the target view of a selected laser line scanner. Such corresponding reference points can help to determine a transformation matrix with higher accuracy than utilizing scanned planes of faces for the alignment. In some examples, the alignment artifactcomprises similar cross-sectional dimensions to an object to be scanned for measurement. As a specific example, the cylinder objectcan comprise a height of 4 inches and a radius of 3 inches. In some such examples, each of the spherescan comprise a diameter of a half inch.is illustrative. In other examples, an alignment artifact may have another configuration.

500 600 600 100 400 6 FIG. During alignment of a laser line scanner, a transformation matrix is determined based at least upon scans of the alignment artifact.depicts a flowchart of an example methodfor determining such a transformation matrix. The methodcan be performed on the laser measurement systemor the laser measurement system, for example.

600 602 500 604 600 The methodcomprises, at, receiving a raw point cloud of the alignment artifactfrom the laser line scanner within a scanner reference frame. At, the methodcomprises transforming the raw point cloud from the scanner reference frame to a global reference frame using a rough transformation. In some examples, the rough transformation can utilize a previously determined transformation matrix. In other examples, the rough transformation of the raw point cloud may be performed in another suitable manner.

600 606 508 500 504 The methodfurther includes, at, finding a plurality of corresponding scanned center points of a set of scanned spheres. As a specific example, the set of scanned spheres can be determined from the rough transformation, and can be optionally based at least upon metadata comprising a set of expected locations of the corresponding center pointsof the alignment artifactfor one or more of the spheres. Any suitable algorithm can be used to find the corresponding scanned center points of the scanned spheres including, for example, RANSAC (random sample consensus), least square sphere fit algorithms, minimum zone sphere fit algorithms, maximum inscribed sphere fit algorithms, minimum circumscribed sphere fit algorithms, and/or suitable combinations thereof.

600 608 600 610 600 508 504 504 Returning, the methodcomprises, at, transforming coordinates of the corresponding scanned center points of the scanned spheres back into the scanner reference frame. Here, the methodincludes performing a best fit transformation between the scanner reference frame and the global reference frame, as indicated at. More particularly, the methodcan use a linear regression to determine the transformation matrix based at least upon the coordinates transformed of the corresponding scanned center points and the expected locations of the corresponding center pointsthat are within a target view of the laser line scanner. In some examples, the linear regression can include a least squares best fit algorithm. In some such examples, a weighted least squares best fit algorithm can be used. In such examples, the spherescan have a weighting based at least upon a proximity of the sphereto the laser line scanner. Alternatively or additionally, a scan of a partial sphere may have a lower weighting than a scan of a full sphere.

2 FIG.B As discussed with reference to, a transformation matrix ([{right arrow over (T)}]) comprises a rotation matrix ({circumflex over (R)}) and a translation vector ({right arrow over (t)}). Further, the rotation matrix comprises a common direction vector ({right arrow over (d)}). As mentioned, the common direction vector is determined before the alignment. Thus, during alignment, the X- and Z-rotation vectors ({right arrow over (X)} {right arrow over (Z)}) of the rotation matrix and the translation vector ({right arrow over (t)}) are variables to be found, for example, in the following least squares best fit equation:

x z Here, corresponding coordinates in the scanner reference frame are represented by {circumflex over (p)}. Further, coordinates in the global reference frame are represented by p, where the x- and z-coordinates are expressed with: {tilde over (p)}=[pp]. It will be noted that a sufficient number of reference points in both the scanner reference frame and the global reference frame can provide an overdetermined system to solve for the X- and Z-rotation vectors of the rotation matrix and the translation vector.

6 FIG. 6 FIG. 600 612 614 600 As can be seen, the above least squares best fit transformation is a linear algebra equation. As such, the transformation matrix can be determined with a single formula instead of the current methods of performing multiple iterative loops to find a best fit transformation. This helps to significantly decrease processing time compared to the current methods. With reference now to, the methodalso comprises, at, saving the transformation matrix. Further, at, the methodcan be configured to repeat the depicted steps to determine one or more corresponding additional transformation matrices for one or more additional laser line scanners of the laser measurement system.is illustrative. In other examples, a transformation matrix may be determined utilizing another suitable equation, such as, a weighted least squares best fit formula, for example.

7 FIG. 700 700 100 400 700 702 illustrates a flowchart of an example methodfor aligning laser line scanners of a laser measurement system. For example, the methodcan be performed on the laser measurement systemor the laser measurement system. The methodoptionally includes performing a calibration procedure to determine a common direction vector for a plurality of laser line scanners on the laser measurement system by averaging a corresponding plurality of individual direction vectors as indicated at. This helps to address potential skew in the plurality of laser line scanners as discussed. In other examples, the common direction vector can be determined in another suitable manner.

700 704 706 700 700 708 700 710 712 As discussed, an alignment artifact attached to a global reference frame is arranged in a laser measurement system during alignment. Further, each feature of the alignment artifact defines a corresponding reference point. Therefore, for at least a first laser line scanner, the methodcomprises, at, obtaining metadata comprising a set of expected locations of the corresponding reference points for a set of features from a plurality of features of the alignment artifact. The set of features comprises at least the features of the alignment artifact that are within a target view of the first laser line scanner. At, the methodcomprises obtaining a raw point cloud of the alignment artifact within a first scanner reference frame of the first laser line scanner. The methodalso includes, at, determining one or more scanned features from the raw point cloud. Further, the methodcomprises determining a location of a corresponding scanned reference point for each scanned feature of the one or more scanned features to form a set of scanned locations of the corresponding scanned reference points, as indicated at. In some examples, the plurality of features of the alignment artifact comprises a plurality of spheres. In such examples, determining the location of the corresponding scanned reference point for each scanned feature of the one or more scanned features comprises determining a corresponding scanned center point for each scanned sphere in a set of scanned spheres as indicated at. Here, the set of scanned spheres include at least the spheres that are within the target view of the first laser line scanner.

700 714 716 718 716 718 6 FIG. The methodalso comprises, at, determining a first transformation matrix to transform coordinates between the first scanner reference frame and the global reference frame. The first transformation matrix is based at least upon the set of expected locations, the set of scanned locations, and the common direction vector. In some examples, determining the first transformation matrix comprises determining a linear regression using the set of expected locations, the set of scanned locations, and the common direction vector, as indicated at. For example, the linear regression can utilize one or more of the formulas discussed with reference to. In some such examples, determining the linear regression can comprise applying a weighted least squares best fit algorithm as indicated at. In some such examples, the features that are closer to the first laser line scanner may have a higher weight than features that are further from the first laser line scanner. In other examples,and/ormay be omitted.

700 719 704 706 708 710 700 720 In some examples, the laser measurement system can further align one or more additional laser line scanners. In such examples, the methodis configured to loop for each additional laser line scanner to be aligned, as indicated at. Additionally, one or more of,,, ormay be performed in a likewise manner as discussed above for the additional laser line scanners. Therefore, the methodalso comprises determining additional transformation matrices for each laser line scanner of a remainder of the plurality of laser line scanners as indicated at. As previously discussed, each of the additional transformation matrices comprises at least the common direction vector.

700 722 724 Additionally, the methodcomprises, at, measuring a portion of a scanned object using at least the first transformation matrix. In the examples where additional transformation matrices are determined, measuring the portion of the scanned object further uses one or more of the additional transformation matrices, as indicated at. In such a manner, one or more of the laser line scanners of the laser measurement system can be aligned so that transforming coordinates transformed from the scanner reference frame do not unintentionally diverge over the length of the scanned object from undesired skew.

8 FIG. 800 800 100 400 800 802 After aligning the laser line scanners, the laser measurement system can be ready to scan for measurement.illustrates a flowchart of an example methodfor utilizing the transformation matrices from the alignment of the laser line scanners. The methodcan be performed on any suitable laser measurement systems, such as the laser measurement systemor the laser measurement system, for example. The methodcomprises, at, obtaining a raw point cloud of an object using a first laser line scanner. The raw point cloud is within a first scanner reference frame of the first laser line scanner. In some examples, the object can comprise an aircraft part, such as a stringer, for example.

804 800 800 802 806 806 800 808 At, the methodcomprises transforming coordinates of the raw point cloud to form a first transformed point cloud based at least upon a first transformation matrix of the first scanner reference frame. As discussed, the first transformation matrix comprises at least a common direction vector. In some examples, the methodcan be configured to form one or more additional transformed point clouds by returning to, as indicated at. In other examples,may be omitted. The methodalso comprises, at, measuring a portion of the object using at least the first transformed point cloud. In examples where additional transformed point clouds are formed, measuring the portion of the object can further use one or more of the additional transformed point clouds. In such a manner, a transformation matrix comprising at least a common direction vector as disclosed herein can help address potential skew in a plurality of laser line scanners of a laser measurement system. Further, utilizing the disclosed alignment artifact with defined corresponding reference points during alignment of the plurality of laser line scanners may result in a more accurate transformation than utilizing an alignment artifact that does not define reference points.

In some embodiments, the examples described herein can be tied to a computing system of one or more computing devices. In particular, aspects of such methods and processes can be implemented as a computer-application program or service, an API, a library, and/or other computer-program product.

9 FIG. 900 100 400 900 schematically shows a non-limiting embodiment of a computing systemthat can enact one or more of the examples described above. For example, the laser measurement systemand/or the laser measurement systemcan utilize the computing systemto perform suitable functions.

900 900 400 900 4 FIG. Computing systemis shown in simplified form. Computing systemcan take the form of one or more personal computers, server computers, tablet computers, network computing devices, mobile computing devices, mobile communication devices (e.g., smart phones), and/or other computing devices. In some examples, the laser measurement systemofcan comprise one or more aspects of the computing system.

900 902 904 906 900 908 910 9 FIG. Computing systemincludes a logic subsystem, a storage subsystem, and an optional display subsystem. Computing systemcan optionally include an input subsystem, a communication subsystem, and/or other computing-related components not shown in.

902 902 902 600 700 800 902 418 4 FIG. Logic subsystemincludes one or more physical devices configured to execute instructions. For example, logic subsystemcan be configured to execute instructions that are part of one or more applications, services, programs, routines, libraries, objects, components, data structures, or other logical constructs. Such instructions can be implemented to perform a task, implement a data type, transform the state of one or more components, achieve a technical effect, or otherwise arrive at a desired result. For example, logic subsystemcan be used to execute instructions to perform the method, the method, and/or the method. As another example, the logic subsystemcan be used to execute instructions to implement the controllerof.

902 902 902 902 902 Logic subsystemcan include one or more processors configured to execute software instructions. Additionally or alternatively, logic subsystemcan include one or more hardware or firmware logic machines configured to execute hardware or firmware instructions. Processors of logic subsystemcan be single-core or multi-core, and the instructions executed thereon can be configured for sequential, parallel, and/or distributed processing. Individual components of logic subsystemoptionally can be distributed among two or more separate devices, which can be remotely located and/or configured for coordinated processing. Aspects of logic subsystemcan be virtualized and executed by remotely accessible, networked computing devices configured in a cloud-computing configuration.

904 902 904 Storage subsystemincludes one or more physical devices configured to hold instructions executable by logic subsystemto implement the methods and processes described herein. When such methods and processes are implemented, the state of storage subsystemcan be transformed—e.g., to hold different data.

904 904 904 Storage subsystemcan include removable and/or built-in devices. Storage subsystemcan include optical memory (e.g., CD, DVD, HD-DVD, Blu-Ray Disc, etc.), semiconductor memory (e.g., RAM, EPROM, EEPROM, etc.), and/or magnetic memory (e.g., hard-disk drive, floppy-disk drive, tape drive, MRAM, etc.), among others. Storage subsystemcan include volatile, nonvolatile, dynamic, static, read/write, read-only, random-access, sequential-access, location-addressable, file-addressable, and/or content-addressable devices.

904 It will be appreciated by those of ordinary skill in the art, without undue experimentation, that storage subsystemincludes one or more physical devices. However, aspects of the instructions described herein alternatively may be propagated by a communication medium (e.g., an electromagnetic signal, an optical signal, etc.) that is not held by a physical device for a finite duration.

902 904 Aspects of logic subsystemand storage subsystemcan be integrated together into one or more hardware-logic components. Such hardware-logic components can include field-programmable gate arrays (FPGAs), program- and application-specific integrated circuits (PASIC/ASICs), program- and application-specific standard products (PSSP/ASSPs), system-on-a-chip (SOC), and complex programmable logic devices (CPLDs), for example.

906 904 904 906 When included, a display subsystemcan be used to present a visual representation of data held by storage subsystem. This visual representation can take the form of a graphic user interface (GUI). As the herein described methods and processes change the data held by the storage subsystem, and thus transform the state of the storage machine, the state of display subsystemcan likewise be transformed to visually represent changes in the underlying data.

906 902 904 When included, a display subsystemcan include one or more display devices utilizing virtually any type of technology. Such display devices can be combined with logic subsystemand/or storage subsystemin a shared enclosure, or such display devices can be peripheral display devices.

908 908 When included, input subsystemcan comprise or interface with one or more user-input devices such as a keyboard, mouse, touch screen, or joystick. In some embodiments, the input subsystemcan comprise or interface with selected natural user input (NUI) componentry. Such componentry can be integrated or peripheral, and the transduction and/or processing of input actions can be handled on- or off-board. Example NUI componentry can include a microphone for speech and/or voice recognition; an infrared, color, stereoscopic, and/or depth camera for machine vision and/or gesture recognition; a head tracker, eye tracker, accelerometer, and/or gyroscope for motion detection and/or intent recognition; as well as electric-field sensing componentry for assessing brain activity.

910 900 910 910 900 910 When included, and without respect to the dynamic and reconfigurable communication system described above, the communication subsystemcan be configured to communicatively couple computing systemwith one or more other computing devices. Communication subsystemcan include wired and/or wireless communication devices compatible with one or more different communication protocols. As non-limiting examples, the communication subsystem can be configured for communication via a wireless telephone network, or a wired or wireless local- or wide-area network. In some embodiments, communication subsystemcan allow computing systemto send and/or receive messages to and/or from other devices via a network such as the Internet. For example, communication subsystemcan be used to receive or send data to another computing system.

Further, the disclosure comprises configurations according to the following examples.

Example 1. A laser measurement system, comprising an alignment artifact attached to a global reference frame, the alignment artifact having a plurality of features, each feature defining a corresponding reference point relative to the global reference frame; a plurality of laser line scanners; and a controller configured to, for at least a first laser line scanner of the plurality of laser line scanners, obtain metadata comprising a set of expected locations of the corresponding reference points for a set of features from the plurality of features, the set of features comprising at least the features of the alignment artifact that are within a target view of the first laser line scanner during a scan, obtain a raw point cloud of the alignment artifact using the first laser line scanner within a first scanner reference frame, determine one or more scanned features from the raw point cloud; determine a location of a corresponding scanned reference point for each scanned feature of the one or more scanned features to form a set of scanned locations of the corresponding scanned reference points, determine a first transformation matrix to transform coordinates between the first scanner reference frame and the global reference frame based at least upon the set of expected locations, the set of scanned locations, and a common direction vector for the plurality of laser line scanners, and store the first transformation matrix for measurement of a scanned object.

Example 2. The laser measurement system of example 1, wherein the controller is configured to determine the first transformation matrix by determining a linear regression using the set of expected locations, the set of scanned locations, and the common direction vector.

Example 3. The laser measurement system of example 2, wherein the controller is configured to determine the linear regression by applying a weighted least squares best fit algorithm.

Example 4. The laser measurement system of example 1, wherein the first transformation matrix comprises a rotation matrix including the common direction vector.

Example 5. The laser measurement system of example 1, wherein the controller is further configured to perform a calibration procedure to determine the common direction vector by averaging a corresponding plurality of individual direction vectors of the plurality of laser line scanners.

Example 6. The laser measurement system of example 1, wherein the controller is further configured to determine additional transformation matrices for each laser line scanner of a remainder of the plurality of laser line scanners, and to store the additional transformation matrices for the measurement of the scanned object.

Example 7. The laser measurement system of example 1, wherein the plurality of features of the alignment artifact comprises a plurality of spheres.

Example 8. The laser measurement system of example 7, wherein the plurality of spheres is arranged around a cylinder object.

Example 9. The laser measurement system of example 7, wherein the controller is configured to determine the location of the corresponding scanned reference point for each scanned feature of the one or more scanned features by determining a corresponding scanned center point for each scanned sphere in a set of scanned spheres.

Example 10. A method for aligning a laser measurement system comprising a plurality of laser line scanners, the method comprising for at least a first laser line scanner of the plurality of laser line scanners, obtaining metadata comprising a set of expected locations of corresponding reference points for a set of features from a plurality of features of an alignment artifact attached to a global reference frame, the set of features comprising at least the features of the alignment artifact that are within a target view of the first laser line scanner; obtaining a raw point cloud of the alignment artifact within a first scanner reference frame of the first laser line scanner; determining one or more scanned features from the raw point cloud; determining a location of a corresponding scanned reference point for each scanned feature of the one or more scanned features to form a set of scanned locations; determining a first transformation matrix to transform coordinates between the first scanner reference frame and the global reference frame based at least upon the set of expected locations, the set of scanned locations, and a common direction vector for the plurality of laser line scanners; and measuring a portion of a scanned object using at least the first transformation matrix.

Example 11. The method of example 10, wherein determining the first transformation matrix comprises determining a linear regression using the set of expected locations, the set of scanned locations, and the common direction vector.

Example 12. The method of example 11, wherein determining the linear regression comprises applying a weighted least squares best fit algorithm.

Example 13. The method of example 10, wherein the first transformation matrix comprises a rotation matrix including the common direction vector.

Example 14. The method of example 10, further comprising performing a calibration procedure to determine the common direction vector by averaging a corresponding plurality of individual direction vectors of the plurality of laser line scanners.

Example 15. The method of example 10, further comprising determining additional transformation matrices for each laser line scanner of a remainder of the plurality of laser line scanners, and wherein measuring the scanned object further uses one or more of the additional transformation matrices.

Example 16. The method of example 10, wherein the plurality of features of the alignment artifact comprises a plurality of spheres, and wherein determining the location of the corresponding scanned reference point for each scanned feature of the one or more scanned features comprises determining a corresponding scanned center point for each scanned sphere in a set of scanned spheres.

Example 17. A laser measurement system, comprising a plurality of laser line scanners; and a controller configured to, for at least a first laser line scanner of the plurality of laser line scanners, obtain a raw point cloud of an object, wherein coordinates of the raw point cloud are within a first scanner reference frame of the first laser line scanner, transform the coordinates of the raw point cloud to form a first transformed point cloud based at least upon a transformation matrix of the first scanner reference frame, the transformation matrix comprising at least a common direction vector for the plurality of laser line scanners, and measure a portion of the object using at least the first transformed point cloud.

Example 18. The laser measurement system of example 17, wherein the controller is further configured to determine the transformation matrix of the first scanner reference frame before obtaining the raw point cloud of the object.

Example 19. The laser measurement system of example 17, wherein the controller is further configured to perform a calibration procedure to determine the common direction vector.

Example 20. The laser measurement system of example 17, wherein the object comprises an aircraft part.

It will be understood that the configurations and/or approaches described herein are exemplary in nature, and that these specific embodiments or examples are not to be considered in a limiting sense, because numerous variations are possible. The specific routines or methods described herein may represent one or more of any number of processing strategies. As such, various acts illustrated and/or described may be performed in the sequence illustrated and/or described, in other sequences, in parallel, or omitted. Likewise, the order of the above-described processes may be changed.

The subject matter of the present disclosure includes all novel and non-obvious combinations and sub-combinations of the various processes, systems and configurations, and other features, functions, acts, and/or properties disclosed herein, as well as any and all equivalents thereof.